| --- |
| base_model: weny22/sum_model_t5_saved |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: sum_model_0318 |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # sum_model_0318 |
|
|
| This model is a fine-tuned version of [weny22/sum_model_t5_saved](https://huggingface.co/weny22/sum_model_t5_saved) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.2129 |
| - Rouge1: 0.1944 |
| - Rouge2: 0.0649 |
| - Rougel: 0.1561 |
| - Rougelsum: 0.1561 |
| - Gen Len: 18.906 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 20 |
| - eval_batch_size: 20 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | 3.5498 | 1.0 | 1071 | 2.4036 | 0.1898 | 0.064 | 0.1515 | 0.1517 | 18.7547 | |
| | 3.1356 | 2.0 | 2142 | 2.3257 | 0.1905 | 0.0632 | 0.152 | 0.1522 | 18.864 | |
| | 2.9964 | 3.0 | 3213 | 2.2863 | 0.1913 | 0.0628 | 0.1533 | 0.1534 | 18.882 | |
| | 2.9052 | 4.0 | 4284 | 2.2622 | 0.1917 | 0.0639 | 0.1546 | 0.1546 | 18.8833 | |
| | 2.8472 | 5.0 | 5355 | 2.2430 | 0.1925 | 0.0638 | 0.1544 | 0.1545 | 18.8893 | |
| | 2.7982 | 6.0 | 6426 | 2.2388 | 0.1937 | 0.0643 | 0.1553 | 0.1554 | 18.894 | |
| | 2.7681 | 7.0 | 7497 | 2.2256 | 0.1952 | 0.0649 | 0.1567 | 0.1567 | 18.9047 | |
| | 2.7501 | 8.0 | 8568 | 2.2202 | 0.1942 | 0.0648 | 0.1556 | 0.1557 | 18.902 | |
| | 2.7305 | 9.0 | 9639 | 2.2150 | 0.1946 | 0.0651 | 0.1563 | 0.1563 | 18.904 | |
| | 2.723 | 10.0 | 10710 | 2.2129 | 0.1944 | 0.0649 | 0.1561 | 0.1561 | 18.906 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.38.2 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
|
|
